This
course provides a broad introduction to machine learning and its applications.
It will introduce students the basic ideas and intuition behind different machine
learning techniques as well as a more formal understanding of how and why they
work. The course will also discuss recent applications of machine learning,
such as to bioinformatics, social computing, and autonomic computing.

This course is designed for CS graduate students and senior undergraduate
students.

Discussion of general concepts and questions concerning the homework
assignments among students is allowed. However, each of you is expected to
work on the homework solutions on your own. Sharing of any part of
solutions is prohibited. If you are unclear about the policy, please consult
with the instructor before you act. Suspected cases of academic
misconduct will be pursued fully in accordance to the Student
Academic Honesty Codeof Thomas J. Watson School of Engineering and Applied
Science, BinghamtonUniversity.

Late Policy:

Each assignment is due at the beginning of class on the due date. Any
assignment received within the next 24 hours will be penalized by 20% of the
full credit; any assignment received within the time between 24 hours and 48
hours pass the deadline is penalized by 50% of the full credit; No assignment
will be accepted after 48 hours pass the deadline. Rare exceptions of this
policy may be made at the discretion of the instructor under demonstrably
circumstances.